gapup-mcp

competitor_pricing_scrape

Read-only

Scrape and parse a competitor pricing page from a URL or domain. Fetches via proxy-aware timedFetch (tries /pricing, /plans, homepage fallback), then extracts: plan names, prices, billing cadence (monthly/annual/usage-based/one-time), key features, free tier presence, enterprise tier, estimated price range. Returns structured pricing tiers. If unfetchable or no pricing found (anti-bot, SPA, auth wall): returns a clear degraded result with warnings and signals — never fake success. ICP: founders, product managers, pricing strategists, competitive intel teams. Proxy-aware (AICI_RESEARCH_PROXY_URL). Cache TTL 6h.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes	Competitor URL or domain (e.g. 'https://notion.so/pricing', 'notion.so', 'https://www.example.com'). For best results, provide the direct pricing page URL.
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`tiers`	Yes
`domain`	Yes
`status`	Yes
`warnings`	Yes
`url_fetched`	Yes
`has_free_tier`	Yes
`pricing_found`	Yes
`quality_score`	Yes
`raw_price_signals`	Yes
`has_enterprise_tier`	Yes
`plan_names_detected`	Yes
`billing_model_signals`	Yes
`estimated_price_range`	Yes

TDQS

A4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds rich behavioral context: proxy-aware fetching, URL fallback logic (/pricing, /plans, homepage), degraded result handling (never fake success), and cache TTL (6h). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured, front-loading the core action and then adding details on edge cases, audience, and technical notes. It is somewhat lengthy but every sentence contributes meaningful information. Could be slightly tighter but still effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (web scraping with fallback logic, caching, degraded results, output schema present), the description covers all key aspects: what it does, how it handles errors, audience, and technical constraints. It is complete for agent selection and invocation without requiring additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (both url and async parameters described). The tool description adds a usage hint for url ('For best results, provide the direct pricing page URL.'), but does not elaborate on async beyond what's in schema. Baseline 3 applies; minimal extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool scrapes and parses competitor pricing pages from a URL or domain. It specifies the extraction fields (plan names, prices, etc.) and the output format. However, it does not explicitly distinguish itself from sibling tools like competitor_pricing_radar, which may have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides an ICP (founders, product managers, etc.) and hints at best use (providing direct pricing page URL). It implies use for scraping specific competitor pages but lacks explicit when-not or alternative tool guidance (e.g., when to use competitor_pricing_radar).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All gapup-mcp tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

Need Help?